Other

What is RNA secondary structure prediction?

What is RNA secondary structure prediction?

The secondary structure prediction algorithm predicts the lowest free energy structure, which is the most probable secondary structure. It also predicts low free energy structures, called suboptimal structures, which suggest possible alternative structures (Zuker, 1989).

What is an RNA Pseudoknot?

RNA pseudoknots are structural motifs in RNA that are increasingly recognized in viral and cellular RNAs. Pseudoknots are formed upon base pairing of a single-stranded region of RNA in the loop of a hairpin to a stretch of complementary nucleotides elsewhere in the RNA chain.

How many types of RNA structure prediction are there?

There are two main types of mainstream RNA secondary structure prediction algorithms. One is the deterministic dynamic programming algorithm. The earliest use of a dynamic programming algorithm is the Nussinov algorithm based on the maximum number of base pairings (Nussinov et al., 1978).

What is the secondary structure of RNA?

The secondary structure of RNA consists of a single polynucleotide. Base pairing in RNA occurs when RNA folds between complementarity regions. Both single- and double-stranded regions are often found in RNA molecules.

What is minimum free energy RNA?

The minimum free energy (MFE) of ribonucleic acids (RNAs) increases at an apparent linear rate with sequence length. Simple indices, obtained by dividing the MFE by the number of nucleotides, have been used for a direct comparison of the folding stability of RNAs of various sizes.

Why is RNA secondary structure important?

For many RNA molecules, the secondary structure is highly important to the correct function of the RNA — often more so than the actual sequence. This fact aids in the analysis of non-coding RNA sometimes termed “RNA genes”.

What is RNA kissing?

RNA kissing interactions, also called loop-loop pseudoknots, occur when the unpaired nucleotides in one hairpin loop, base pair with the unpaired nucleotides in another hairpin loop. When the hairpin loops are located on separate RNA molecules, their intermolecular interaction is called a kissing complex.

What is a Pseudoknot structure?

First recognized in the turnip yellow mosaic virus [1], a pseudoknot is an RNA structure that is minimally composed of two helical segments connected by single-stranded regions or loops (Figure 1). This causes the formation of a second stem and loop, resulting in a pseudoknot with two stems and two loops (Figure 1C).

What is an example of secondary structure of RNA?

There are many secondary structure elements of functional importance to biological RNA’s; some famous examples are the Rho-independent terminator stem-loops and the tRNA cloverleaf.

What is the purpose of RNA secondary structure?

RNA transcripts fold into secondary structures via intricate patterns of base pairing. These secondary structures impart catalytic, ligand binding, and scaffolding functions to a wide array of RNAs, forming a critical node of biological regulation.

What is the concept of free energy?

Free energy, in thermodynamics, energy-like property or state function of a system in thermodynamic equilibrium. Free energy is an extensive property, meaning that its magnitude depends on the amount of a substance in a given thermodynamic state.

How are pseudoknots used in RNA structure prediction?

RNA pseudoknots are a class of base pairing structures that appear in many viruses and may comprise as much as 10% of all RNA structures [3]. However, including the complete repertoire of pseudoknots in RNA structure prediction can drastically increase the demands on computational resources [4].

How to predict pseudoknots using heuristic modeling?

Here, an algorithm utilizing structure mapping and thermodynamics is introduced for RNA pseudoknot prediction that finds the minimum free energy and identifies information about the flexibility of the RNA.

Is it possible to predict the secondary structure of RNA?

Predicting RNA secondary structure is often the first step to determining the structure of RNA. Prediction approaches have historically avoided searching for pseudoknots because of the extreme combinatorial and time complexity of the problem. Yet neglecting pseudoknots limits the utility of such approaches.

Which is the best approach to the pseudoknot problem?

Vsfold5 is a unique approach that makes it possible to transition directly to the pseudoknot (PK) problem. The worst case introduces at most a factor N to the computation time (known as time complexity), where N is the sequence length.